Spaces:
Sleeping
Sleeping
File size: 3,293 Bytes
98985f3 24c122a bbc0512 f3369dd 24c122a d35776c c89cc71 d35776c a17b6c0 d35776c e3dfd55 6475fdc c89cc71 e3dfd55 6475fdc a17b6c0 d35776c 238547c d35776c 98985f3 2789d18 6475fdc c89cc71 6475fdc 24c122a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
from transformers import AutoTokenizer
import gradio as gr
def formatarr(input):
return "["+",".join(str(x) for x in input)+"]"
def tokenize(input_text):
llama_tokens = llama_tokenizer(input_text, add_special_tokens=True)["input_ids"]
llama3_tokens = llama3_tokenizer(input_text, add_special_tokens=True)["input_ids"]
mistral_tokens = mistral_tokenizer(input_text, add_special_tokens=True)["input_ids"]
gpt2_tokens = gpt2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
gpt_neox_tokens = gpt_neox_tokenizer(input_text, add_special_tokens=True)["input_ids"]
falcon_tokens = falcon_tokenizer(input_text, add_special_tokens=True)["input_ids"]
phi2_tokens = phi2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
phi3_tokens = phi3_tokenizer(input_text, add_special_tokens=True)["input_ids"]
t5_tokens = t5_tokenizer(input_text, add_special_tokens=True)["input_ids"]
gemma_tokens = gemma_tokenizer(input_text, add_special_tokens=True)["input_ids"]
command_r_tokens = command_r_tokenizer(input_text, add_special_tokens=True)["input_ids"]
qwen_tokens = qwen_tokenizer(input_text, add_special_tokens=True)["input_ids"]
codeqwen_tokens = codeqwen_tokenizer(input_text, add_special_tokens=True)["input_ids"]
results = {
"LLaMa-1/LLaMa-2": llama_tokens,
"LLaMa-3": llama3_tokens,
"Mistral": mistral_tokens,
"GPT-2/GPT-J": gpt2_tokens,
"GPT-NeoX": gpt_neox_tokens,
"Falcon": falcon_tokens,
"Phi-1/Phi-2": phi2_tokens,
"Phi-3": phi3_tokens,
"T5": t5_tokens,
"Gemma": gemma_tokens,
"Command-R": command_r_tokens,
"Qwen/Qwen1.5": qwen_tokens,
"CodeQwen": codeqwen_tokens,
}
toks = ""
for model, tokens in results.items():
toks += f"\n{model} gets {len(tokens)} tokens: {formatarr(tokens)}"
return toks
if __name__ == "__main__":
llama_tokenizer = AutoTokenizer.from_pretrained(
"TheBloke/Llama-2-7B-fp16"
)
llama3_tokenizer = AutoTokenizer.from_pretrained(
"unsloth/llama-3-8b"
)
mistral_tokenizer = AutoTokenizer.from_pretrained(
"mistral-community/Mistral-7B-v0.2"
)
gpt2_tokenizer = AutoTokenizer.from_pretrained(
"gpt2"
)
gpt_neox_tokenizer = AutoTokenizer.from_pretrained(
"EleutherAI/gpt-neox-20b"
)
falcon_tokenizer = AutoTokenizer.from_pretrained(
"tiiuae/falcon-7b"
)
phi2_tokenizer = AutoTokenizer.from_pretrained(
"microsoft/phi-2"
)
phi3_tokenizer = AutoTokenizer.from_pretrained(
"microsoft/Phi-3-mini-4k-instruct"
)
t5_tokenizer = AutoTokenizer.from_pretrained(
"google/flan-t5-xxl"
)
gemma_tokenizer = AutoTokenizer.from_pretrained(
"alpindale/gemma-2b"
)
command_r_tokenizer = AutoTokenizer.from_pretrained(
"CohereForAI/c4ai-command-r-plus"
)
qwen_tokenizer = AutoTokenizer.from_pretrained(
"Qwen/Qwen1.5-7B"
)
codeqwen_tokenizer = AutoTokenizer.from_pretrained(
"Qwen/CodeQwen1.5-7B"
)
iface = gr.Interface(
fn=tokenize, inputs=gr.Textbox(label="Input Text", lines=12), outputs="text"
)
iface.launch()
|